Guy Cohen on Celeste AI and the Future of Commerce Media

1. How is the integration of GenAI reshaping the landscape of commerce media, and what implications does this have for traditional marketing strategies?

The integration of Generative AI (GenAI) is significantly reshaping the landscape of commerce media by introducing intelligent systems like Celeste AI that can analyze complex data, provide real-time insights, and automate tasks, ultimately leading to smarter and faster decision-making for marketers. Skai believes GenAI offers the opportunity to remove complexity from media and introduce a new future for marketers. For example, Celeste AI is designed to transform how brands and agencies navigate commerce media. It leverages Skai’s proprietary data intelligence, real-time signals from over 200 publishers, and cross-channel insights to deliver smarter, faster decisions. Skai’s platform now transforms the growing complexity of commerce media, with its surge in channels, publishers, ad formats, and data, into actionable strategies by unifying and interpreting information.

This transformation has several implications for traditional marketing strategies:

● Increased need for intelligent tools to handle complexity: As commerce media becomes more intricate with more channels, publishers, ad formats, and data, traditional methods of managing information become insufficient. GenAI capabilities are necessary to unify, interpret, and act on this complexity.

● Shift from manual data analysis to automated insights: Marketers will move from sifting through dashboards to interacting directly with data through natural language, asking questions and receiving immediate, actionable insights. 

● Focus shift towards strategic work: By automating routine tasks like reporting and performance monitoring, GenAI allows marketing professionals to focus on envisioning, strategizing, and creating. For example, Celeste can automate tasks that previously took hours or days, such as creating weekly, monthly, and QBR reports.

● Emphasis on faster decision-making: GenAI provides real-time insights and recommendations, enabling marketers to act more quickly and precisely. Speed to insight is crucial, especially in performance channels where trends shift rapidly.

● Importance of integrating and leveraging diverse data: Success in commerce media demands more than just access to information; it requires the ability to unify and interpret various data sources like first-party data, publisher insights, and competitive intelligence. GenAI helps connect the dots between insights and business outcomes by leveraging data.

● Need to adapt to AI-driven optimization: Traditional strategies might become less effective as AI continuously learns and improves campaign optimization based on historical performance, competitive trends, and channel synergies.

2. What challenges do organizations face in unifying data from multiple sources, such as first-party data, publisher insights, and competitive intelligence, to inform marketing strategies?

One of the biggest challenges in advertising today is the sheer volume of data generated across multiple platforms. Traditional advertising tools often struggle to process and interpret this data efficiently, leaving marketers bogged down in inefficient decision-making. While Skai's platform aims to seamlessly integrate omnichannel commerce media, combining first-party advertiser data, publisher insights, competitive intelligence, and digital shelf data, the general challenge remains for organizations using more traditional or less integrated tools. Many traditional platforms are siloed by channel, requiring separate logins and disjointed reporting, which leads to inefficiencies and missed opportunities. Unifying data from diverse sources requires the ability to connect disparate data points and transform them into actionable insights. Marketers often have to sift through complex dashboards and spreadsheets to make decisions.

3. What role does AI play in automating routine tasks, and how does this shift the focus of marketing professionals toward more strategic initiatives?

AI, particularly GenAI agents like Celeste, plays a significant role in automating routine tasks in marketing. Celeste can automate time-consuming tasks such as budget allocation, creative adjustments, and performance tracking. It can also handle tasks like generating reports (weekly, monthly, QBR) in minutes, which previously took hours or days. AI-powered systems can also automate bid management. By automating these mundane activities, AI frees up valuable time for marketing teams to focus on higher-level activities such as strategy development and innovation. This shift allows people to do what they do best: dream and envision, strategize, and create. With AI handling executional complexity, organizations can become more agile.

4. How can AI assist in transforming complex, fragmented data into actionable insights for more effective campaign planning and execution?

AI, with its ability to analyze vast amounts of data, can transform complex, fragmented data into actionable insights by aggregating signals from multiple advertising platforms. Celeste AI, for example, aggregates signals from over 200 publishers, competitive insights, and cross-channel performance to deliver tailored recommendations. AI can identify patterns and optimization opportunities that human analysts might miss. It can provide real-time, context-aware recommendations tailored to each campaign’s unique needs, such as adjusting budget allocations, optimizing bids, or tweaking creative strategies. Unlike traditional tools that might provide static reports, AI actively engages with the marketer’s workflow by delivering tailored recommendations, helping them act decisively and efficiently. Marketers can interact directly with their data by asking tactical and strategic questions and receive immediate, actionable insights. Celeste is designed to deliver real, actionable guidance: budget reallocations, keyword recommendations, SKU-level insights, anomaly detection, and channel-specific strategy prompts.

5. In what ways can AI-driven insights contribute to optimizing marketing performance and achieving higher ROI across different platforms?

AI-driven insights contribute to optimizing marketing performance and achieving higher ROI across different platforms in several ways:

● Improving budget allocation: AI can analyze performance data and recommend optimal budget reallocations across retail media, paid search, and social platforms to maximize ROI.

● Enhancing campaign optimization: AI provides granular insights into factors like keyword performance, audience engagement, and creative effectiveness, enabling marketers to fine-tune their campaigns for better results. 

● Identifying growth opportunities: AI can uncover hidden opportunities by aggregating insights from across the marketing stack and connecting dots that may otherwise go unnoticed, helping marketers refine strategies and identify new segments faster.

● Providing tailored recommendations: AI delivers tailored recommendations based on a brand’s specific needs, enabling marketers to act more quickly and precisely.

● Enabling real-time decision-making: AI provides real-time insights and recommendations, allowing marketers to make immediate, data-driven actions to seize opportunities or mitigate issues.

● Continuously learning and improving: AI is designed to continuously learn and improve with each interaction, ensuring it can make the best decisions possible based on historical performance, competitive trends, and channel synergies.

● Measuring incremental impact: AI-powered tools can help measure the true incremental impact of media spend, providing clarity on which campaigns are driving real growth and enabling more effective budget allocation.

6. What emerging trends do you foresee in the convergence of AI and commerce media over the next few years?

Several emerging trends are foreseen in the convergence of AI and commerce media:

● Evolution to multi-agent systems: AI agents like Celeste, currently acting as a single agent, will evolve into multi-agent systems, with each agent specializing in distinct tasks across planning, forecasting, activation, and measurement.

● Seamless integration with client-side AI: AI platforms will increasingly integrate and collaborate with clients’ own GenAI capabilities and custom AI agents, creating a truly intelligent commerce media ecosystem.

● Increased specialization of AI: AI tools will become more specific to different marketing roles within a brand or company, providing tailored results based on individual needs and objectives.

● AI as the new User Interface (UI): The primary way marketers interact with technology will shift towards natural language interfaces powered by AI, making complex systems more accessible and easier to use. As AI becomes the new UI, marketers need to focus on intelligence when selecting tech partners.

● Focus on enabling technologies: AI will be seen less as a standalone tool and more as an enabling technology that constantly evolves and improves with more data and user interaction, allowing clients to build more value in the future.

● Development of client-specific AI agents: Clients will increasingly want to create their own AI agents within platforms, introducing their own data types, processes, and artifacts to tailor the AI’s capabilities to their specific needs. For instance, Skai’s clients are asking to make Celeste “their” Celeste.

● Continued focus on efficiency, performance, and growth: The core value propositions of AI in commerce media will remain focused on driving efficiency and productivity, improving performance and optimization, and uncovering new growth opportunities for brands.

● The future is about intelligence, not just features: Commerce media won’t be defined by features alone, but by the intelligence driving them.